Real-time driver drowsiness feedback improves driver alertness and self-reported driving performance
نویسندگان
چکیده
منابع مشابه
Real-time driver drowsiness feedback improves driver alertness and self-reported driving performance.
Driver drowsiness has been implicated as a major causal factor in road accidents. Tools that allow remote monitoring and management of driver fatigue are used in the mining and road transport industries. Increasing drivers' own awareness of their drowsiness levels using such tools may also reduce risk of accidents. The study examined the effects of real-time blink-velocity-derived drowsiness fe...
متن کاملA Real Time Driver Drowsiness Detection System
Driving with drowsiness is one of the main causes of traffic accidents. Driver fatigue is a significant factor in a large number of vehicle accidents. The development of technologies for detecting or preventing drowsiness at the wheel is a major challenge in the field of accident avoidance systems. Due to the hazard that drowsiness presents on the road, methods need to be developed for countera...
متن کاملReal-time Nonintrusive Detection of Driver Drowsiness
Driver drowsiness is one of the major causes of serious traffic accidents, which makes this an area of great socioeconomic concern. Continuous monitoring of drivers’ drowsiness thus is of great importance to reduce drowsiness-caused accidents. This proposed research developed a real-time, nonintrusive driver drowsiness detection system by building biosensors on the automobile steering wheel and...
متن کاملNon Intrusive Drunken Driving and Driver Drowsiness
The aim of our project is to provide a real time non-intrusive driver drowsiness detection to prevent the rapidly growing accidents caused by sleepy or drunk driver. We are going to merge the 2 requirements for safe driving in a single equipment. The car does not function unless the two conditions of safe driving are satisfied. Bio signals, such as brain waves, pulsation waves, and heart beat a...
متن کاملDriver Drowsiness Detection by Identification of Yawning and Eye Closure
Today most accidents are caused by drivers’ fatigue, drowsiness and losing attention on the road ahead. In this paper, a system is introduced, using RGB-D cameras to automatically identify drowsiness and give warning. In this system two important modules have been utilized simultaneously to identify the state of driver’s mouth and eyes for detecting drowsiness. At first, using the depth informa...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Accident Analysis & Prevention
سال: 2015
ISSN: 0001-4575
DOI: 10.1016/j.aap.2015.03.041